{"id":24415,"date":"2022-03-16T08:35:34","date_gmt":"2022-03-16T14:35:34","guid":{"rendered":"https:\/\/saluddigital.com\/?p=24415"},"modified":"2025-10-21T10:08:09","modified_gmt":"2025-10-21T16:08:09","slug":"las-principales-caracteristicas-de-los-algoritmos-de-salud","status":"publish","type":"post","link":"https:\/\/saluddigital.com\/en\/big-data\/las-principales-caracteristicas-de-los-algoritmos-de-salud\/","title":{"rendered":"The main characteristics of health algorithms"},"content":{"rendered":"
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Scientists from the University of Florida Health published an article in PLOS Digital Health, on the main attributes of algorithms applied in health.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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The article precisely details the importance of defining the ideal characteristics that algorithms applied in health should have in order to provide the best benefits and tools to patients and health professionals. Specialists highlight six desiderata in the development of health algorithms, that is, ideal and desired aspects.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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The six desideratas are contemplated by the specialists of the University of Florida Health are:<\/p>

  1. Explainable: That is, it conveys the relative importance of the characteristics in determining the results.<\/li>
  2. Dynamic: Capture temporary changes in physiological signals and clinical events.<\/li>
  3. Accurate: Using high-resolution multimodal data and the use of complex architecture.<\/li>
  4. Autonomous: That is to say that it is capable of achieving learning with minimal supervision and its execution without human input.<\/li>
  5. Fair: Evaluate and mitigate implicit bias and social inequity.<\/li>
  6. Reproducible: Externally and prospectively validated and shared with academic communities.<\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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    The study authors identified eight examples of algorithms for performing the analysis, of which all met the accuracy criteria, six were self-contained, five met the fair criteria, four were explainable, and only three were reproducible. However, the dynamic feature was not applicable for any of the analyzed algorithms.<\/p>

    The authors apply that, if an algorithm meets the objective of covering these six characteristics or criteria, it can enhance the quality of medical care and greater benefits will be achieved for physicians, patients and researchers.<\/p>

    See the full article at the following link:<\/p>

    https:\/\/journals.plos.org\/digitalhealth\/article?id=10.1371\/journal.pdig.0000006<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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    \n\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t BIBLIOGRAPHY<\/a>\n\t\t\t\t\t<\/div>\n\n\t\t\t\t\t

    PLOS DIGITAL HEALTH<\/strong><\/p>

    https:\/\/journals.plos.org\/digitalhealth\/article?id=10.1371\/journal.pdig.0000006<\/a><\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

    Cient\u00edficos de University of Florida Health, publicaron un art\u00edculo en PLOS Digital Health, sobre los principales atributos de los algoritmos aplicados en salud. El art\u00edculo detalla con precisi\u00f3n la importancia de definir las caracter\u00edsticas ideales que deben tener los algoritmos aplicados en salud para brindar los mejores beneficios y herramientas a pacientes y profesionales de la salud. Los especialistas destacan seis desideratas en el desarrollo de algoritmos en salud, es decir aspectos ideales y deseados. Las seis desideratas son contempladas por los especialistas de University of Florida Health son: Explicable: Es decir que transmita la importancia relativa de las caracter\u00edsticas en la determinaci\u00f3n de los resultados. Din\u00e1mico: Capturar cambios temporales en se\u00f1ales fisiol\u00f3gicas y eventos cl\u00ednicos. Preciso: Que utilice datos multimodales de alta resoluci\u00f3n y el uso de arquitectura compleja. Aut\u00f3noma: Es decir que sea capaz de lograr un aprendizaje con m\u00ednima supervisi\u00f3n y su ejecuci\u00f3n sin aporte humano. Justo: Que eval\u00fae, y mitigue el sesgo impl\u00edcito y la inequidad social. Reproducible: Validada externa y prospectivamente y compartida con las comunidades acad\u00e9micas. Los autores del estudio identificaron ocho ejemplos de algoritmos para llevar a cabo el an\u00e1lisis, de los cuales todos cumplieron con los criterios de precisi\u00f3n, seis fueron aut\u00f3nomos, cinco cumplieron los criterios de justo, cuatro fueron explicables y solo tres sufren reproducibles. Sin embargo, la caracter\u00edstica de din\u00e1mico no fue aplicable para ninguno de los algoritmos analizados. Los autores aplican que, si un algoritmo cumple con el objetivo de cubrir estas seis caracter\u00edsticas o criterios, pueden potenciar la calidad de la atenci\u00f3n m\u00e9dica y se alcanzar\u00e1n mayores beneficios a m\u00e9dico, pacientes e investigadores. Consulta el art\u00edculo completo en el siguiente enlace: https:\/\/journals.plos.org\/digitalhealth\/article?id=10.1371\/journal.pdig.0000006 BIBLIOGRAF\u00cdA PLOS DIGITAL HEALTH https:\/\/journals.plos.org\/digitalhealth\/article?id=10.1371\/journal.pdig.0000006<\/p>","protected":false},"author":1,"featured_media":24417,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3399,156,160,1418],"tags":[145],"class_list":["post-24415","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-analitica","category-big-data","category-noticias","category-resena-de-publicaciones-cientificas","tag-noticias"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/24415","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/comments?post=24415"}],"version-history":[{"count":0,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/24415\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media\/24417"}],"wp:attachment":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media?parent=24415"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/categories?post=24415"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/tags?post=24415"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}